An optimized filter design approach for enhancing imaging quality in industrial linear accelerator.
J Xray Sci Technol
; 32(4): 1137-1150, 2024.
Article
in En
| MEDLINE
| ID: mdl-38875073
ABSTRACT
BACKGROUND:
The polychromatic X-rays generated by a linear accelerator (Linac) often result in noticeable hardening artifacts in images, posing a significant challenge to accurate defect identification. To address this issue, a simple yet effective approach is to introduce filters at the radiation source outlet. However, current methods are often empirical, lacking scientifically sound metrics.OBJECTIVE:
This study introduces an innovative filter design method that optimizes filter performance by balancing the impact of ray intensity and energy on image quality. MATERIALS ANDMETHODS:
Firstly, different spectra under various materials and thicknesses of filters were obtained using GEometry ANd Tracking (Geant4) simulation. Subsequently, these spectra and their corresponding incident photon counts were used as input sources to generate different reconstructed images. By comprehensively comparing the intensity differences and noise in images of defective and non-defective regions, along with considering hardening indicators, the optimal filter was determined.RESULTS:
The optimized filter was applied to a Linac-based X-ray computed tomography (CT) detection system designed for identifying defects in graphite materials within high-temperature gas-cooled reactor (HTR), with defect dimensions of 2âmm. After adding the filter, the hardening effect reduced by 22%, and the Defect Contrast Index (DCI) reached 3.226.CONCLUSION:
The filter designed based on the parameters of Average Difference (AD) and Defect Contrast Index (DCI) can effectively improve the quality of defect images.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Particle Accelerators
/
Tomography, X-Ray Computed
/
Equipment Design
Language:
En
Journal:
J Xray Sci Technol
/
J. X-ray sci. technol
/
Journal of x-ray science and technology
Journal subject:
RADIOLOGIA
Year:
2024
Document type:
Article
Affiliation country:
China
Country of publication:
Países Bajos